Jack W. Kent

6.9k total citations
97 papers, 2.6k citations indexed

About

Jack W. Kent is a scholar working on Genetics, Molecular Biology and Physiology. According to data from OpenAlex, Jack W. Kent has authored 97 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Genetics, 36 papers in Molecular Biology and 17 papers in Physiology. Recurrent topics in Jack W. Kent's work include Genetic Associations and Epidemiology (33 papers), Adipose Tissue and Metabolism (13 papers) and Genetic Mapping and Diversity in Plants and Animals (12 papers). Jack W. Kent is often cited by papers focused on Genetic Associations and Epidemiology (33 papers), Adipose Tissue and Metabolism (13 papers) and Genetic Mapping and Diversity in Plants and Animals (12 papers). Jack W. Kent collaborates with scholars based in United States, Australia and United Kingdom. Jack W. Kent's co-authors include John Blangero, Laura Almasy, Thomas D. Dyer, Joanne E. Curran, Harald H.H. Göring, Melanie A. Carless, Shelley A. Cole, David C. Glahn, Anthony G. Comuzzie and Juan M. Peralta and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Jack W. Kent

97 papers receiving 2.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jack W. Kent United States 31 836 831 339 276 257 97 2.6k
Melanie A. Carless United States 28 490 0.6× 1.0k 1.3× 550 1.6× 235 0.9× 196 0.8× 81 2.7k
Rita M. Cantor United States 31 639 0.8× 868 1.0× 211 0.6× 276 1.0× 118 0.5× 66 2.7k
Elizabeth T. Cirulli United States 28 1.1k 1.3× 1.1k 1.3× 242 0.7× 265 1.0× 119 0.5× 50 2.8k
Jo Knight United Kingdom 33 917 1.1× 1.0k 1.2× 357 1.1× 460 1.7× 128 0.5× 106 3.3k
Chia‐Hsiang Chen Taiwan 34 814 1.0× 989 1.2× 582 1.7× 247 0.9× 139 0.5× 153 3.2k
Oleksandr Frei Norway 27 1.7k 2.0× 824 1.0× 389 1.1× 221 0.8× 124 0.5× 102 2.9k
Alkes L. Price United States 6 2.6k 3.1× 1.0k 1.2× 183 0.5× 267 1.0× 147 0.6× 6 3.8k
Audrey C. Papp United States 33 444 0.5× 1.7k 2.1× 387 1.1× 357 1.3× 328 1.3× 57 3.9k
Ravindranath Duggirala United States 36 1.4k 1.7× 1.2k 1.5× 802 2.4× 529 1.9× 239 0.9× 116 4.4k
Silviu‐Alin Bacanu United States 33 1.3k 1.6× 983 1.2× 226 0.7× 303 1.1× 88 0.3× 109 3.3k

Countries citing papers authored by Jack W. Kent

Since Specialization
Citations

This map shows the geographic impact of Jack W. Kent's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jack W. Kent with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jack W. Kent more than expected).

Fields of papers citing papers by Jack W. Kent

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jack W. Kent. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jack W. Kent. The network helps show where Jack W. Kent may publish in the future.

Co-authorship network of co-authors of Jack W. Kent

This figure shows the co-authorship network connecting the top 25 collaborators of Jack W. Kent. A scholar is included among the top collaborators of Jack W. Kent based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jack W. Kent. Jack W. Kent is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chernoff, Meytal, Dayana Delgado, Tong Lin, et al.. (2023). Sequencing-based fine-mapping and in silico functional characterization of the 10q24.32 arsenic metabolism efficiency locus across multiple arsenic-exposed populations. PLoS Genetics. 19(1). e1010588–e1010588. 5 indexed citations
2.
Levine, Todd, David Saperstein, Alan Pestronk, & Jack W. Kent. (2017). Identification of a Novel Immune Mediated Cause for Small Fiber Neuropathy (P4.137). Neurology. 88(16_supplement). 4 indexed citations
3.
Hodgson, Karen, Laura Almasy, Emma Knowles, et al.. (2016). The genetic basis of the comorbidity between cannabis use and major depression. Addiction. 112(1). 113–123. 28 indexed citations
4.
Kent, Jack W.. (2016). Pathway-based analyses. BMC Genetics. 17(S2). 5–5. 4 indexed citations
5.
Dager, Alecia D., Dean McKay, Jack W. Kent, et al.. (2014). Shared Genetic Factors Influence Amygdala Volumes and Risk for Alcoholism. Neuropsychopharmacology. 40(2). 412–420. 40 indexed citations
6.
Sprooten, Emma, Emma Knowles, Dean McKay, et al.. (2014). Common genetic variants and gene expression associated with white matter microstructure in the human brain. NeuroImage. 97. 252–261. 24 indexed citations
7.
Glahn, David C., Jeff T. Williams, Dean McKay, et al.. (2014). Discovering Schizophrenia Endophenotypes in Randomly Ascertained Pedigrees. Biological Psychiatry. 77(1). 75–83. 25 indexed citations
8.
Hernandez-Escalante, Victor M., Edna J. Nava‐González, V. Saroja Voruganti, et al.. (2014). Replication of obesity and diabetes-related SNP associations in individuals from Yucatán, México. Frontiers in Genetics. 5. 380–380. 10 indexed citations
9.
McKay, Dean, Peter Kochunov, Matthew D. Cykowski, et al.. (2013). Correction: Sincich and Horton, Independent Projection Streams from Macaque Striate Cortex to the Second Visual Area and Middle Temporal Area. Journal of Neuroscience. 33(50). 19734.1–19734. 1 indexed citations
10.
Curran, Joanne E., Dean McKay, Anderson M. Winkler, et al.. (2013). Identification of Pleiotropic Genetic Effects on Obesity and Brain Anatomy. Human Heredity. 75(2-4). 136–143. 20 indexed citations
11.
Curran, Joanne E., Thomas D. Dyer, Jack W. Kent, et al.. (2013). Variation in osteoarthritis biomarker serum comp levels in Mexican Americans is associated with SNPs in a region of chromosome 22q encompassing MICAL3, BCL2L13, and BID. Osteoarthritis and Cartilage. 21. S172–S172. 3 indexed citations
12.
13.
Johnson, Matthew P., Shaun P. Brennecke, Christine East, et al.. (2012). Genome-Wide Association Scan Identifies a Risk Locus for Preeclampsia on 2q14, Near the Inhibin, Beta B Gene. PLoS ONE. 7(3). e33666–e33666. 96 indexed citations
14.
Kochunov, Peter, David C. Glahn, L. Elliot Hong, et al.. (2012). P-selectin Expression Tracks Cerebral Atrophy in Mexican-Americans. Frontiers in Genetics. 3. 65–65. 11 indexed citations
15.
Johnson, Matthew P., Shaun P. Brennecke, Ann‐Charlotte Iversen, et al.. (2012). OS046. Genome-wide association scans identify novel maternalsusceptibility loci for preeclampsia. Pregnancy Hypertension. 2(3). 202–202. 2 indexed citations
16.
Glahn, David C., Joanne E. Curran, Anderson M. Winkler, et al.. (2011). High Dimensional Endophenotype Ranking in the Search for Major Depression Risk Genes. Biological Psychiatry. 71(1). 6–14. 125 indexed citations
17.
Kent, Jack W., Thomas D. Dyer, Harald H.H. Göring, & John Blangero. (2007). Type I error rates in association versus joint linkage/association tests in related individuals. Genetic Epidemiology. 31(2). 173–177. 9 indexed citations
18.
Bastarrachea, Raúl A., Joanne E. Curran, Jack W. Kent, et al.. (2006). Vinculando la respuesta inflamatoria, la obesidad y la diabetes con la sobrecarga (estrés) del retículo endoplásmico a través de las acciones de la selenoproteína S. 14(2). 89–101. 2 indexed citations
19.
Bastarrachea, Raúl A., et al.. (2005). El receptor de insulina como objetivo farmacogenómico: potenciando su señalización intracelular. 13(4). 180–189. 1 indexed citations
20.
Kent, Jack W. & Thomas E. Richardson. (1998). FLUORESCENTLY LABELLED, MULTIPLEXED CHLOROPLAST MICROSATELLITES FOR HIGH-THROUGHPUT PATERNITY ANALYSIS IN PINUS RADIATA. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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